code: def extend_minibatch_with(
      self,
      tensorized_datapoint: TensorizedGraph2Seq,
      partial_minibatch: Dict[str, Any],
  ) -> bool:
      continue_adding = self.__gnn_model.extend_minibatch_with(
          tensorized_datapoint.encoder_data,
          partial_minibatch["encoder_mb_data"],
      )
      continue_adding &= self.__decoder_model.extend_minibatch_with(
          tensorized_datapoint.decoder_data,
          partial_minibatch["decoder_mb_data"],
      )
      return continue_adding
  
imports: from typing_extensions import Final, TypedDict
  import torch
  from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel, ModuleWithMetrics
  from ptgnn.baseneuralmodel.utils.data import enforce_not_None
  from ptgnn.neuralmodels.gnn.graphneuralnetwork import GraphNeuralNetwork, GraphNeuralNetworkModel
  from ptgnn.neuralmodels.gnn.structs import GnnOutput, GraphData, TensorizedGraphData
  from ptgnn.neuralmodels.reduceops import AbstractVarSizedElementReduce, ElementsToSummaryRepresentationInput, MultiheadSelfAttentionVarSizedElementReduce, SimpleVarSizedElementReduce
  from ptgnn.neuralmodels.sequence.grucopydecoder import DecoderData, GruCopyingDecoder, GruCopyingDecoderModel, TokenizedOutput
label_desc: Use image node_id 6 for calling the Graph2Seq obj's underlying member method code with example usage: obj.extend_minibatch_with(tensorized_datapoint, partial_minibatch) and returns: continue_adding